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Whom to Test? Active Sampling Strategies for Managing COVID-19
This paper presents methods to choose individuals to test for infection ...
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Spoiled for Choice? Personalized Recommendation for Healthcare Decisions: A Multi-Armed Bandit Approach
Online healthcare communities provide users with various healthcare inte...
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Dynamic Bidding for Advance Commitments in Truckload Brokerage Markets
Truckload brokerages, a 100 billion/year industry in the U.S., plays the...
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Optimal Learning for Sequential Decision Making for Expensive Cost Functions with Stochastic Binary Feedbacks
We consider the problem of sequentially making decisions that are reward...
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An optimal learning method for developing personalized treatment regimes
A treatment regime is a function that maps individual patient informatio...
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Functional Frank-Wolfe Boosting for General Loss Functions
Boosting is a generic learning method for classification and regression....
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The Knowledge Gradient with Logistic Belief Models for Binary Classification
We consider sequential decision making problems for binary classificatio...
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A Knowledge Gradient Policy for Sequencing Experiments to Identify the Structure of RNA Molecules Using a Sparse Additive Belief Model
We present a sparse knowledge gradient (SpKG) algorithm for adaptively s...
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